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25–42 of 42 · Most stars

a basic OpenSCENARIO player

  • openscenario
  • opendrive
  • trafficscenarios
  • simulationscenarios

Fulldex: all your favourite Pokémon games in one launcher, in widescreen at 60 fps on PC, Mac, Steam Deck, Android, iPhone and Switch. DS: Black 2, White 2, Black, White, HeartGold, SoulSilver, Platinum, Diamond, Pearl. GBA: Emerald, Ruby, Sapphire, FireRed, LeafGreen, Ultra Violet. 3DS coming soon. RetroAchievements. Bring your own ROMs.

  • homebrew
  • nds
  • nintendo-switch
  • pokemon

A lightweight, high-performance, industrial-grade cross-language logging library (C++/Java/C#/Kotlin/TS/Python/Go), battle-tested in Honor of Kings.

  • cross-platform
  • high-performance
  • java
  • logging

A decompiled PC Port of Super Mario Galaxy, intended to work on Windows, Linux, MacOS, Android, and iOS/iPadOS.

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

An unordered C++ data container providing fast iteration/insertion/erasure while maintaining pointer/iterator validity to non-erased elements regardless of insertions/erasures. Provides higher-performance than std:: library containers for high-modification scenarios with unordered data.

lightweight TIFF reader/writer library (C/C++)

  • lib
  • file-format
  • tiff-files
  • tiff-encoder

An open source, cross-platform game engine designed for indie developers.

  • chillisource-game-engine
  • 2d-game-engine
  • 3d-game-engine
  • cpp11

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.